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1. Dynamics of racial disparities in all-cause mortality during the COVID-19 pandemic

   https://doi.org/10.1073/pnas.2210941119  

   Aschmann, Hélène E.; Riley, Alicia R.; Chen, Ruijia; Chen, Yea-Hung; Bibbins-Domingo, Kirsten; Stokes, Andrew C.; Glymour, M. Maria; Kiang, Mathew V. (October 2022, Proceedings of the National Academy of Sciences)

   As research documenting disparate impacts of COVID-19 by race and ethnicity grows, little attention has been given to dynamics in mortality disparities during the pandemic and whether changes in disparities persist. We estimate age-standardized monthly all-cause mortality in the United States from January 2018 through February 2022 for seven racial/ethnic populations. Using joinpoint regression, we quantify trends in race-specific rate ratios relative to non-Hispanic White mortality to examine the magnitude of pandemic-related shifts in mortality disparities. Prepandemic disparities were stable from January 2018 through February 2020. With the start of the pandemic, relative mortality disadvantages increased for American Indian or Alaska Native (AIAN), Native Hawaiian or other Pacific Islander (NHOPI), and Black individuals, and relative mortality advantages decreased for Asian and Hispanic groups. Rate ratios generally increased during COVID-19 surges, with different patterns in the summer 2021 and winter 2021/2022 surges, when disparities approached prepandemic levels for Asian and Black individuals. However, two populations below age 65 fared worse than White individuals during these surges. For AIAN people, the observed rate ratio reached 2.25 (95% CI = 2.14, 2.37) in October 2021 vs. a prepandemic mean of 1.74 (95% CI = 1.62, 1.86), and for NHOPI people, the observed rate ratio reached 2.12 (95% CI = 1.92, 2.33) in August 2021 vs. a prepandemic mean of 1.31 (95% CI = 1.13, 1.49). Our results highlight the dynamic nature of racial/ethnic disparities in mortality and raise alarm about the exacerbation of mortality inequities for Indigenous groups due to the pandemic. 

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2. Vascular comorbidities worsen prognosis of patients with heart failure hospitalised with COVID-19

   https://doi.org/10.1136/openhrt-2021-001668  

   Mok, Jacob; Malpartida, Juan Carlos; O'Dell, Kimberly; Davis, Joshua; Gao, Cuilan; Manyam, Harish (June 2021, Open Heart)

   null (Ed.)

   Background Prior diagnosis of heart failure (HF) is associated with increased length of hospital stay (LOS) and mortality from COVID-19. Associations between substance use, venous thromboembolism (VTE) or peripheral arterial disease (PAD) and its effects on LOS or mortality in patients with HF hospitalised with COVID-19 remain unknown. Objective This study identified risk factors associated with poor in-hospital outcomes among patients with HF hospitalised with COVID-19. Methods Case–control study was conducted of patients with prior diagnosis of HF hospitalised with COVID-19 at an academic tertiary care centre from 1 January 2020 to 28 February 2021. Patients with HF hospitalised with COVID-19 with risk factors were compared with those without risk factors for clinical characteristics, LOS and mortality. Multivariate regression was conducted to identify multiple predictors of increased LOS and in-hospital mortality in patients with HF hospitalised with COVID-19. Results Total of 211 patients with HF were hospitalised with COVID-19. Women had longer LOS than men (9 days vs 7 days; p<0.001). Compared with patients without PAD or ischaemic stroke, patients with PAD or ischaemic stroke had longer LOS (7 days vs 9 days; p=0.012 and 7 days vs 11 days, p<0.001, respectively). Older patients (aged 65 and above) had increased in-hospital mortality compared with younger patients (adjusted OR: 1.04; 95% CI 1.00 to 1.07; p=0.036). Prior diagnosis of VTE increased mortality more than threefold in patients with HF hospitalised with COVID-19 (adjusted OR: 3.33; 95% CI 1.29 to 8.43; p=0.011). Conclusion Vascular diseases increase LOS and mortality in patients with HF hospitalised with COVID-19. 

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3. Telemedicine and Healthcare Disparities: A cohort study in a large healthcare system in New York City during COVID-19

   https://doi.org/10.1093/jamia/ocaa217  

   Chunara, Rumi; Zhao, Yuan; Chen, Ji; Lawrence, Katharine; Testa, Paul A; Nov, Oded; Mann, Devin M (August 2020, Journal of the American Medical Informatics Association)

   Abstract Objective Through the coronavirus disease 2019 (COVID-19) pandemic, telemedicine became a necessary entry point into the process of diagnosis, triage and treatment. Racial and ethnic disparities in health care have been well documented in COVID-19 with respect to risk of infection and in-hospital outcomes once admitted, and here we assess disparities in those who access healthcare via telemedicine for COVID-19 . Materials and Methods Electronic health record data of patients at New York University Langone Health between March 19th and April 30, 2020 were used to conduct descriptive and multilevel regression analyses with respect to visit type (telemedicine or in-person), suspected COVID diagnosis and COVID test results. Results Controlling for individual and community-level attributes, Black patients had 0.6 times the adjusted odds (95%CI:0.58-0.63) of accessing care through telemedicine compared to white patients, though they are increasingly accessing telemedicine for urgent care, driven by a younger and female population. COVID diagnoses were significantly more likely for Black versus white telemedicine patients. Discussion There are disparities for Black patients accessing telemedicine, however increased uptake by young, female Black patients. Mean income and decreased mean household size of Zip code were also significantly related to telemedicine use. Conclusion Telemedicine access disparities reflect those in in-person healthcare access. Roots of disparate use are complex and reflect individual, community, and structural factors, including their intersection; many of which are due to systemic racism. Evidence regarding disparities that manifest through telemedicine can be used to inform tool design and systemic efforts to promote digital health equity. 

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4. Development and validation of predictive models for COVID-19 outcomes in a safety-net hospital population

   https://doi.org/10.1093/jamia/ocac062  

   Hao, Boran; Hu, Yang; Sotudian, Shahabeddin; Zad, Zahra; Adams, William G.; Assoumou, Sabrina A.; Hsu, Heather; Mishuris, Rebecca G.; Paschalidis, Ioannis C. (May 2022, Journal of the American Medical Informatics Association)

   Abstract ObjectiveTo develop predictive models of coronavirus disease 2019 (COVID-19) outcomes, elucidate the influence of socioeconomic factors, and assess algorithmic racial fairness using a racially diverse patient population with high social needs. Materials and MethodsData included 7,102 patients with positive (RT-PCR) severe acute respiratory syndrome coronavirus 2 test at a safety-net system in Massachusetts. Linear and nonlinear classification methods were applied. A score based on a recurrent neural network and a transformer architecture was developed to capture the dynamic evolution of vital signs. Combined with patient characteristics, clinical variables, and hospital occupancy measures, this dynamic vital score was used to train predictive models. ResultsHospitalizations can be predicted with an area under the receiver-operating characteristic curve (AUC) of 92% using symptoms, hospital occupancy, and patient characteristics, including social determinants of health. Parsimonious models to predict intensive care, mechanical ventilation, and mortality that used the most recent labs and vitals exhibited AUCs of 92.7%, 91.2%, and 94%, respectively. Early predictive models, using labs and vital signs closer to admission had AUCs of 81.1%, 84.9%, and 92%, respectively. DiscussionThe most accurate models exhibit racial bias, being more likely to falsely predict that Black patients will be hospitalized. Models that are only based on the dynamic vital score exhibited accuracies close to the best parsimonious models, although the latter also used laboratories. ConclusionsThis large study demonstrates that COVID-19 severity may accurately be predicted using a score that accounts for the dynamic evolution of vital signs. Further, race, social determinants of health, and hospital occupancy play an important role. 

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5. Disparities in Hemoglobin A _1c Levels in the First Year After Diagnosis Among Youths With Type 1 Diabetes Offered Continuous Glucose Monitoring

   https://doi.org/10.1001/jamanetworkopen.2023.8881  

   Addala, Ananta; Ding, Victoria; Zaharieva, Dessi P.; Bishop, Franziska K.; Adams, Alyce S.; King, Abby C.; Johari, Ramesh; Scheinker, David; Hood, Korey K.; Desai, Manisha; et al (April 2023, JAMA Network Open)

   Importance Continuous glucose monitoring (CGM) is associated with improvements in hemoglobin A 1c (HbA 1c ) in youths with type 1 diabetes (T1D); however, youths from minoritized racial and ethnic groups and those with public insurance face greater barriers to CGM access. Early initiation of and access to CGM may reduce disparities in CGM uptake and improve diabetes outcomes. Objective To determine whether HbA 1c decreases differed by ethnicity and insurance status among a cohort of youths newly diagnosed with T1D and provided CGM. Design, Setting, and Participants This cohort study used data from the Teamwork, Targets, Technology, and Tight Control (4T) study, a clinical research program that aims to initiate CGM within 1 month of T1D diagnosis. All youths with new-onset T1D diagnosed between July 25, 2018, and June 15, 2020, at Stanford Children’s Hospital, a single-site, freestanding children’s hospital in California, were approached to enroll in the Pilot-4T study and were followed for 12 months. Data analysis was performed and completed on June 3, 2022. Exposures All eligible participants were offered CGM within 1 month of diabetes diagnosis. Main Outcomes and Measures To assess HbA 1c change over the study period, analyses were stratified by ethnicity (Hispanic vs non-Hispanic) or insurance status (public vs private) to compare the Pilot-4T cohort with a historical cohort of 272 youths diagnosed with T1D between June 1, 2014, and December 28, 2016. Results The Pilot-4T cohort comprised 135 youths, with a median age of 9.7 years (IQR, 6.8-12.7 years) at diagnosis. There were 71 boys (52.6%) and 64 girls (47.4%). Based on self-report, participants’ race was categorized as Asian or Pacific Islander (19 [14.1%]), White (62 [45.9%]), or other race (39 [28.9%]); race was missing or not reported for 15 participants (11.1%). Participants also self-reported their ethnicity as Hispanic (29 [21.5%]) or non-Hispanic (92 [68.1%]). A total of 104 participants (77.0%) had private insurance and 31 (23.0%) had public insurance. Compared with the historical cohort, similar reductions in HbA 1c at 6, 9, and 12 months postdiagnosis were observed for Hispanic individuals (estimated difference, −0.26% [95% CI, −1.05% to 0.43%], −0.60% [−1.46% to 0.21%], and −0.15% [−1.48% to 0.80%]) and non-Hispanic individuals (estimated difference, −0.27% [95% CI, −0.62% to 0.10%], −0.50% [−0.81% to −0.11%], and −0.47% [−0.91% to 0.06%]) in the Pilot-4T cohort. Similar reductions in HbA 1c at 6, 9, and 12 months postdiagnosis were also observed for publicly insured individuals (estimated difference, −0.52% [95% CI, −1.22% to 0.15%], −0.38% [−1.26% to 0.33%], and −0.57% [−2.08% to 0.74%]) and privately insured individuals (estimated difference, −0.34% [95% CI, −0.67% to 0.03%], −0.57% [−0.85% to −0.26%], and −0.43% [−0.85% to 0.01%]) in the Pilot-4T cohort. Hispanic youths in the Pilot-4T cohort had higher HbA 1c at 6, 9, and 12 months postdiagnosis than non-Hispanic youths (estimated difference, 0.28% [95% CI, −0.46% to 0.86%], 0.63% [0.02% to 1.20%], and 1.39% [0.37% to 1.96%]), as did publicly insured youths compared with privately insured youths (estimated difference, 0.39% [95% CI, −0.23% to 0.99%], 0.95% [0.28% to 1.45%], and 1.16% [−0.09% to 2.13%]). Conclusions and Relevance The findings of this cohort study suggest that CGM initiation soon after diagnosis is associated with similar improvements in HbA 1c for Hispanic and non-Hispanic youths as well as for publicly and privately insured youths. These results further suggest that equitable access to CGM soon after T1D diagnosis may be a first step to improve HbA 1c for all youths but is unlikely to eliminate disparities entirely. Trial Registration ClinicalTrials.gov Identifier: NCT04336969 

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